A critical evaluation of handling uncertainty in Big Data processing

Abstract

Big Data is a modern economic and social transformation driver all over the world. The selection has reached a tipping point in terms of big technological advancements that could usher in new ones. It's about making decisions, taking charge of our health, our cities, our wallets, and our education. While the amount, diversity, speed, and reliability of data has increased, so has the complexity of the data (Amzal et al., 2006). Our ability to identify the "value of information through Big Data" will have the most impact. As a result of the resolution of large data concerns, Big Data is revolutionising the IT sector Software vendors in many industries are unable to move forward with dependability and scalability, Information on the project. With the help of relational databases, the explanation for why business requires adequate atomic transactions in the business sector. As a result, to benefit from both technology, advantages, and solutions. Big Data, which refers to databases that are too huge to be processed with current database administration tools, is gaining traction in a variety of significant applications, including internet search, business, social networking, genomics, and meteorology [2]. This concept highlights key research challenges and the promise of data-driven optimization that organically integrates fuzzy, machine learning, and deep learning for decision-making under uncertainty, and identifies potential research opportunities in the business field of Bayesian optimization under uncertainty through a modern data lens. Big Data is a big issue for science and database data mining. Here, we look at the fascinating activities that my community has been doing at this conference to talk about the Big Data problem. As a result, the central focus is linking Big Data to individuals in numerous ways.